Temperament, Ability, and Interests Predict Important Real World Choices

Introduction and overview SAPA methodology Results References

Temperament, ability, and interests predict important real world choices

William Revelle and David Condon Part of a Symposium: Motivation as a basic personality process. Organized by Luke Smillie and Joshua Wilt Annual meeting of the Society for the Study of Motivation

Personality, Motivation and Cognition Laboratory Department of Psychology Northwestern University Evanston, Illinois USA

1 / 41

Chicago, May 24, 2012 Introduction and overview SAPA methodology Results References

Outline

1 Introduction and overview Personality and Motivation Beyond Aﬀect, Behavior, Cognition and Desire: Temperament, Ability and Interests A need for integrative studies

2 SAPA methodology Conceptual overview Technical Overview

3 Results Analytical Technique TAI and motivational choice

2 / 41 Introduction and overview SAPA methodology Results References

The study of personality includes the study of motivation

1 Personality is the coherent patterning over time and space of Affect, Behavior, Cognition and Desire. Items in most personality tests may be organized in terms of their relative emphasis on the ABCDs. We have examined the coherency of ABCDs over short periods of time (e.g., the patterning of energetic and affective changes during the day over several weeks using text messaging). We have also examined it cross sectionally to examine long time choice behavior with meaningful outcomes. 2 Personality and motivation Traditional personality measures emphasize average levels of ABCDs. Personality traits reflect sensitivities to motivationally salient stimuli. Personality traits are the first derivatives of personality states in reaction to motivationally salient stimuli. Short term: Affective reactions and goal directed behavior Long term: Meaningful life choices: College major and occupation 3 / 41 Introduction and overview SAPA methodology Results References

Personality and Temperament

Hogan (1982) distinguishes between personality as identity and personality as reputation. To this we would add actions. 1 Identity How we see ourselves Studies of the structure of self report 2 Reputation How others see us Studies of the structure of peer report 3 Actions What we actually do Studies of the residues of our choices and our actions. One important outcome is choice of college major. Another is the choice of occupation.

4 / 41 Introduction and overview SAPA methodology Results References Going beyond the ABCDs: Personality as Temperament, Ability, and Interests

1 Temperament: what we usually do Identity, Reputation, and Actions Aﬀective, Cognitive and Behavioral reactions to situations: the “Big 5” (Goldberg, 1990), the “Giant 3” (Eysenck, 1990) 2 Ability: What we can do Measures of intellectual ability – life as an intelligence test (Deary, Penke & Johnson, 2010; Gottfredson, 1997; Horn & Cattell, 1966; Johnson & Bouchard, 2005) 3 Interests: What we like to do 6 dimensions: Realistic, Investigative, Artistic, Social, Enterprising, Conventional (aka RIASEC Holland, 1996) 2 dimensions (e.g., people vs. things/facts vs. ideas, Prediger & Vansickle, 1992) of interests

5 / 41 Introduction and overview SAPA methodology Results References

Traditional model of Temperament, Abilities, and Interests

A C Temperament Temperament 2- 5 dimensions reflecting E N individual differences in Affect, O Behavior, Cognition, Desire

Ability V P Abilities g 1 g 2 gf gc R Interests R 2 broad dimensions organizing C I 6-8 speciﬁc interests Interests E A 1 People vs. Things S 2 Facts vs Ideas 6 / 41 Introduction and overview SAPA methodology Results References

Personality as Temperament, Ability, and Interests

1 It has long been known that Temperament, Ability and Interests (TAI) are interrelated predictors of long term outcomes (Kelly & Fiske, 1950). Unfortunately, the study of interests has been relegated to vocational counselors Ability has been studied by educational psychologists and Industrial Organizational psychologists. Need to integrate these in a general theory of personality and motivated choice. 2 A few groups do try to integrate temperament and ability These include Lubinski & Benbow (2000); Lubinski, Webb, Morelock & Benbow (2001); Lubinski & Benbow (2006) Ackerman (1997), Ackerman & Heggestad (1997) Kuncel, Campbell & Ones (1998); Kuncel, Hezlett & Ones (2001); Kuncel, Crede & Thomas (2005)

7 / 41 Introduction and overview SAPA methodology Results References

Traditional model of Temperament, Abilities, and Interests

A C Temperament E N O

V P Abilities g Outcome

R C I Interests E A S

8 / 41 Introduction and overview SAPA methodology Results References

Motivation involves choice

1 Motivational models emphasize intensity as well as direction Performance models emphasize eﬃciency in any one task How many resources are available for a particular task 2 Direction of behavior (aka resource allocation) emphasizes choice Dynamic models of choice (the Dynamics of Action) from Atkinson & Birch (1970) or a reparameterization (the Cues-Tendency-Action model) by Revelle (1986) emphasize that behaviors inhibit each other. For computer simulations of choice behavior using the Cues-Tendency-Action (CTA) model see Fua, Horswill, Ortony & Revelle (2009); Fua, Revelle & Ortony (2010)

9 / 41 Introduction and overview SAPA methodology Results References

Motivation involves choice between incompatible outcomes

A C Temperament Outcome1 E N O

V P Abilities g Outcome2

R C I Interests Outcome3 E A S

10 / 41 Introduction and overview SAPA methodology Results References

A need for integrative studies

Prior work has shown that there is a need to integrate Temperament, Abilities and Interests. But how to do it? To integrate the areas requires large sample sizes, ease of data collection, and a diverse subject population. Some do this through meta analysis, some use broad based national samples. Is it possible for single labs to do integrative studies?

11 / 41 Introduction and overview SAPA methodology Results References

How to do integrative studies?

Problem of small samples sizes based upon college undergraduates. Typical subject pools are neither large enough nor diverse enough. Expensive to get access to large and diverse populations Exceptions include national and international survey samples using preselected items: National Longitudinal Study of Youth (NLSY) Program for International Student Assessment (PISA) German Socio-Economic Panel Is it possible to do large based sampling with tailored items? Yes, use the web.

12 / 41 Introduction and overview SAPA methodology Results References

Synthetic Aperture Personality Assessment (SAPA)

Using the web and open source materials to collect data on temperament, ability and interests Synthetically form large covariance matrices from smaller subsets of items Each subject given ≈ 50 personality, 10 interest, and 14-16 ability items sampled from the larger pool. Total pool of items > 1000 ≈ 400 personality items primarily from International Personality Item Pool Goldberg (1999) 92 interest items for Oregon Vocational Interest Scales (Pozzebon, Visser, Ashton, Lee & Goldberg, 2010) 80 ability items (home brewed at NU) Demographic items include age, sex, education, race, country, college major, occupation (if appropriate) Resulting sample sizes > 50, 000 − 250, 000 College major, occupational status and interest items added in 9/10 Data to be summarized include ≈ 65, 000 participants

13 / 41 Introduction and overview SAPA methodology Results References

Method

1 Synthetic Aperture Personality Assessment (Revelle, Wilt & Rosenthal, 2010) forms large covariance matrices by sampling items across people ≈ 120/day particpants are recruited to test.personality-project.org Each participant is given 60-70 items Total set of items being analyzed > 500 2 Item content being sampled 100 “IPIP” Big 5 items ≈ 200 other temperamental items 56-80 home brewed ability items 92 Oregon Vocational Interest items (ORVIS) 3 Although > 200, 000 participants have been run in all, we will report only those data from the last 65,000 4 Demographic information included Age, Gender Level of education College major and broad ﬁeld (if appropriate) Occupation (if appropriate) 14 / 41 Introduction and overview SAPA methodology Results References

SAPA: what the subject sees

ab B

15 / 41 Introduction and overview SAPA methodology Results References

SAPA: what the subject sees

ac C

16 / 41 Introduction and overview SAPA methodology Results References

SAPA: what the subject sees

ad D

17 / 41 Introduction and overview SAPA methodology Results References

SAPA: what the subject sees

bc C

18 / 41 Introduction and overview SAPA methodology Results References

SAPA: what the subject sees

bd D

19 / 41 Introduction and overview SAPA methodology Results References

SAPA: what the subject sees

cd D

20 / 41 Introduction and overview SAPA methodology Results References

SAPA: what the experimenter sees: A Synthetic matrix

ab B

ac bc C

ad bd cd D

21 / 41 Introduction and overview SAPA methodology Results References

SAPA: Technical overview

1 n x n synthetic covariance matrices are formed by giving p items to Np subjects N Total number of subjects n Total number of items in synthetic matrix p Probability of any item being given pN Number of subjects taking any one item p2N Number of subjects for any pair of items 2 Basic statistics Data are Massively Missing at Random Means and Variances are based upon pN subjects Covariances are based upon p2N subjects 3 Power of large samples and sampling of items 100-150 people per day => 40,000 subjects per year 700-1000 subjects/week By varying p, one can prototype items rapidly.

22 / 41 Introduction and overview SAPA methodology Results References

International Personality Item Pool (IPIP) Big 5: sample items

Conscientiousness Do things according to a plan. Agreeableness Inquire about others’ well-being. Neuroticism/Stability Have frequent mood swings. Openness Am full of ideas Extraversion Make friends easily

23 / 41 Introduction and overview SAPA methodology Results References

Oregon Vocational Interest Scales: sample items

Adventure Would like to be a professional athlete. Altruism Like to care for sick people. Analytic Would like to be a chemist. Artistic Create works of art. Erudition Would like to be a translator or interpreter. Leadership Like to make important things happen. Organization Would like to be the ﬁnancial oﬃcer for a company. Practical Would like to care for cattle or horses.

24 / 41 Introduction and overview SAPA methodology Results References

Cognitive Ability items

1 Self reported values on standardized tests SAT Verbal SAT Quantitative ACT 2 Open source items developed for the SAPA project Analytic Alphanumeric sequences Matrix Analogous to Raven’s matrices 3 D rotation Diﬃculty created by number of rotations Verbal Basic vocabulary Full IQ Weighted sum score of the parts

25 / 41 Introduction and overview SAPA methodology Results References

Analytical approach: All analyses done in R

1 R: An international collaboration http://R-cran.org 2 R: The open source - public domain version of S+ 3 R: Written by statistician (and all of us) for statisticians (and the rest of us) 4 R: Not just a statistics system, also an extensible language. This means that as new statistics are developed they tend to appear in R far sooner than elsewhere. For example, a recent issue of Pschological Methods had at least three articles with examples or supplementary work done in R R facilitates asking questions that have not already been asked. 5 Special functions for SAPA have been written in R and are included in the psych package.

26 / 41 Introduction and overview SAPA methodology Results References

Analytical reporting

1 Given the sample sizes, statistical significance is not an issue, but rather the size of the effects. 2 Correlation is an appropriate effect size measure Correlations between continuous variables are reported as Pearson r Correlations between dichotomous variables are reported as tetrachoric correlations Correlations between continuous and dichotomous are reported as biserial These last two correlations make assumptions of normal distributions of latent traits 3 Data displays are graphical techniques for showing the complex, multivariate structure of the data Correlation strength reported as a “heat map” with positive correlations shaded as progressively darker shades of blue, negative correlations as darker shades of red. Some multidimensional plots

27 / 41 Introduction and overview SAPA methodology Results References

Analysis of Temperament, Ability, Interests

1 Big 5 scale scores used an Item Response Theory (IRT) algorithm With complete data, IRT and simple sum scores are almost identical. SAPA data are Massively Missing at Random and are better estimated using IRT techniques. Two parameter model: item diﬃculty, item location One parameter model: item diﬃculty 2 Ability measures SATV, SATQ, SATW and ACT were self reported iq measure was based upon IRT analysis and scoring

28 / 41 Introduction and overview SAPA methodology Results References

Temperament, Ability and Interests

Agreeable 1 Conscientious Stability 0.8 Extraversion Intellect 0.6 SATV SATQ SATW 0.4 ACT FullIQ 0.2 ANiq MXiq 0 R3Diq VEdiq Erudition -0.2 Analysis Production -0.4 Artistic Organization -0.6 Adventure Leadership Altruism -0.8

-1 ACT ANiq MXiq SATV FullIQ VEdiq SATQ R3Diq SATW Artistic Intellect Stability Altruism Analysis Erudition Adventure Agreeable Production Leadership Extraversion Organization Conscientious 29 / 41 Introduction and overview SAPA methodology Results References

Choice of college major reﬂects temperament, abilities and interests

1 Undergraduate majors/concentration provide feedback to students based upon performance. 2 Performance reﬂects both ability and time spent on the task Students choose majors which reinforce their talents Interests grow in response to feedback 3 Although many students can do well in many majors, they end up choosing those majors that maximally meet their needs. 4 Multiple ways of displaying these data Majors sorted by ability Majors sorted by a particular temperament (e.g., conscientiousness) Majors in a multi-dimensional space of abilities x temperament

30 / 41 Introduction and overview SAPA methodology Results References

Choosing majors as selection, optimization, and compensation

1 Traits and abilities are independent at individual level This is seen in the plot of all the TAI variables based upon individual 2 Majors draw for certain constellations of traits Selection, Optimization, and Compensation (Baltes & Baltes, 1990) Sorting of majors by TAI dimensions 3 Choice of major selects for constellations This is seen in the plot of the personality dimensions at the aggregate level of majors

31 / 41 Introduction and overview SAPA methodology Results References

College major sorted by Intelligence (top and bottom 10 majors)

Majors by IQ genderAgreeable Stability AnalysisOrganizationLeadership ConscientiousExtraversion IntellectFullIQ Adventure AltruismEruditionArtistic TEIQ 1 Physics -30 -19 -9 -14 10 27 43 8 61 -5 -4 -11 27 1 -10 Mathematics -21 -17 -9 -17 3 14 32 -18 37 3 -15 -32 -1 1 -1 0.8 Chem.Bio.Eng -23 -12 2 -8 4 9 31 25 32 -1 -3 -19 23 4 -10 Neuroscience -3 -12 -5 -11 -4 18 29 -1 25 -7 13 7 13 -28 3 0.6 Electrical.Eng -43 -14 3 -8 10 10 28 15 34 10 -1 -18 -1 -1 -3 Computer.Programming -43 -23 -10 -19 7 10 27 -2 39 9 0 -28 4 -4 -21 0.4 Mechanical.Eng -47 -14 1 -6 10 12 27 44 42 20 14 -13 2 -5 -5 Economics -25 -14 -2 -3 6 14 26 12 20 26 25 -13 6 -7 -4 0.2 Chemistry -10 -9 4 -7 3 12 24 -11 46 5 6 -4 11 1 -1 Music -16 -1 -9 -6 0 16 24 3 2 -13 4 -6 18 46 -13 0 Criminology -1 1 9 4 3 0 -13 14 -10 -6 1 -16 -5 -8 11 Other.Community.Social.Svss 20 14 5 3 3 -3 -13 -5 -4 13 6 21 -4 -12 3 -0.2 Social.Work 26 19 7 7 1 -9 -16 -20 -14 2 -4 30 -6 -9 12 K.preK.Edu 49 11 4 -7 -5 -16 -16 -15 -20 -11 -27 -1 -11 1 0 -0.4 Nursing 37 15 16 7 -1 -9 -18 -10 -6 -4 -22 19 -19 -12 -1 Criminal.Justice.Corrections -5 2 14 5 2 -5 -18 33 -11 3 1 -2 -7 -24 1 -0.6 Human.Development.Family 19 12 8 4 0 -15 -18 3 6 11 5 29 15 6 1 Major.NA -8 -15 -22 -5 -9 -14 -19 5 -6 -20 -6 -16 -12 -2 -17 -0.8 Health.Svcs.Admin 28 15 21 5 0 -5 -21 -7 -14 10 -3 13 -6 -13 7 Medical.Assisting 34 12 16 7 0 -10 -33 -12 -5 18 -10 18 -8 -9 8 -1 32 / 41 Introduction and overview SAPA methodology Results References

College major sorted by Conscientiousness (top and bottom 10 )

Majors by Conscientiousness gender AgreeableConscientiousExtraversionStabilityIntellectFullIQ AdventureAnalysisOrganizationLeadershipAltruismEruditionArtistic TEIQ 1 Health.Svcs.Admin 28 15 21 5 0 -5 -21 -7 -14 10 -3 13 -6 -13 7 Biz.Admin.Mgmt -11 3 18 10 9 0 -8 -6 -7 30 17 -6 -14 -10 12 0.8 Nursing 37 15 16 7 -1 -9 -18 -10 -6 -4 -22 19 -19 -12 -1 Medical.Assisting 34 12 16 7 0 -10 -33 -12 -5 18 -10 18 -8 -9 8 0.6 Edu.Administration 5 9 15 12 12 6 0 9 0 17 7 9 11 18 19 Criminal.Justice.Corrections -5 2 14 5 2 -5 -18 33 -11 3 1 -2 -7 -24 1 0.4 Accounting -4 -3 13 -5 3 -10 2 -4 -1 40 4 -21 -1 -12 -6 Health.Sciences.General 14 11 12 3 -1 -7 -10 -2 1 1 -13 12 -11 -3 -2 0.2 Other.Medicine.Allied.Health 16 11 10 3 3 -6 -6 1 3 -6 -9 19 -16 -14 6 Elementary.Edu 35 17 9 4 -3 -10 -4 -16 -31 -15 -16 20 -1 -13 10 0 Mathematics -21 -17 -9 -17 3 14 32 -18 37 3 -15 -32 -1 1 -1 Physics -30 -19 -9 -14 10 27 43 8 61 -5 -4 -11 27 1 -10 -0.2 Computer.Programming -43 -23 -10 -19 7 10 27 -2 39 9 0 -28 4 -4 -21 Other.Language.LitStudies 6 -4 -10 -11 -1 17 21 4 -2 -4 5 -2 34 6 -7 -0.4 Other.PerfVisual.Art -3 -4 -11 -5 -6 12 7 4 -11 -10 -7 -10 4 31 -29 Graphic.Arts 1 -5 -12 -8 -3 11 5 4 -11 0 -16 -23 16 33 -8 -0.6 Fine.Studio 11 -5 -16 -8 -8 17 10 -6 -12 -15 -16 -21 16 40 9 Fiction.Writing 6 -7 -16 -11 -12 23 11 -7 -11 2 2 -28 19 35 -6 -0.8 Philosophy -17 -15 -17 -8 5 27 24 -3 20 -10 8 -9 19 -2 -20 Major.NA -8 -15 -22 -5 -9 -14 -19 5 -6 -20 -6 -16 -12 -2 -17 -1 33 / 41 Introduction and overview SAPA methodology Results References

College major sorted by Extraversion (top and bottom 10 majors)

Majors by Extraversion genderAgreeableConscientiousExtraversionStabilityIntellectFullIQ AdventureAnalysisOrganizationLeadershipAltruismEruditionArtistic TEIQ 1 PR.Advertising 15 8 1 18 -2 -1 -9 -10 -14 -4 18 -12 7 13 12 Marketing -8 1 3 13 5 -2 2 1 -14 14 22 -13 3 6 14 0.8 Physical.Edu -13 5 3 12 11 -13 -12 21 -18 -14 -1 -7 -27 -25 21 Edu.Administration 5 9 15 12 12 6 0 9 0 17 7 9 11 18 19 0.6 Communications.MediaStudies 6 -1 -3 11 -1 4 -4 -15 -17 -6 10 -18 16 15 2 Biz.Admin.Mgmt -11 3 18 10 9 0 -8 -6 -7 30 17 -6 -14 -10 12 0.4 Drama.Theater 6 6 -8 10 -4 19 6 -6 -22 -20 14 -2 10 37 10 Other.Communications 8 6 2 9 -1 -2 3 7 -15 -12 5 -4 11 9 -1 0.2 Secondary.Edu 0 9 6 8 5 6 -2 7 0 1 15 24 7 4 -1 Nursing 37 15 16 7 -1 -9 -18 -10 -6 -4 -22 19 -19 -12 -1 0 Computer.Eng -39 -13 -1 -9 10 10 24 14 34 17 11 -12 11 11 -1 Other.Language.LitStudies 6 -4 -10 -11 -1 17 21 4 -2 -4 5 -2 34 6 -7 -0.2 Neuroscience -3 -12 -5 -11 -4 18 29 -1 25 -7 13 7 13 -28 3 Fiction.Writing 6 -7 -16 -11 -12 23 11 -7 -11 2 2 -28 19 35 -6 -0.4 Other.CIS -23 -8 -5 -12 3 6 17 -4 22 7 11 -14 -4 -2 -9 English 9 -7 -8 -13 -9 24 17 -17 -8 -11 -11 0 39 15 -4 -0.6 CIS.General -37 -15 -1 -13 6 5 17 3 26 14 8 -14 1 -3 -12 Physics -30 -19 -9 -14 10 27 43 8 61 -5 -4 -11 27 1 -10 -0.8 Mathematics -21 -17 -9 -17 3 14 32 -18 37 3 -15 -32 -1 1 -1 Computer.Programming -43 -23 -10 -19 7 10 27 -2 39 9 0 -28 4 -4 -21 -1

34 / 41 Introduction and overview SAPA methodology Results References

College major sorted by Stabilty–Neuroticsm (top and bottom 10 )

Majors by Stability gender AgreeableConscientiousExtraversionStability IntellectFullIQ AdventureAnalysisOrganizationLeadershipAltruismEruditionArtistic TEIQ 1 MgmtInfoSystems -29 -6 7 -1 16 14 14 18 8 4 17 7 -19 10 18 Edu.Administration 5 9 15 12 12 6 0 9 0 17 7 9 11 18 19 0.8 Other.Eng.Tech.Major -33 -9 3 -1 11 9 16 31 20 14 13 -9 1 6 -9 Physical.Edu -13 5 3 12 11 -13 -12 21 -18 -14 -1 -7 -27 -25 21 0.6 Electrical.Eng -43 -14 3 -8 10 10 28 15 34 10 -1 -18 -1 -1 -3 Mechanical.Eng -47 -14 1 -6 10 12 27 44 42 20 14 -13 2 -5 -5 0.4 Computer.Eng -39 -13 -1 -9 10 10 24 14 34 17 11 -12 11 11 -1 Physics -30 -19 -9 -14 10 27 43 8 61 -5 -4 -11 27 1 -10 0.2 Industrial.Eng -31 -11 2 -2 10 4 8 13 -1 19 -10 2 -11 -4 -3 Biz.Admin.Mgmt -11 3 18 10 9 0 -8 -6 -7 30 17 -6 -14 -10 12 0 Neuroscience -3 -12 -5 -11 -4 18 29 -1 25 -7 13 7 13 -28 3 K.preK.Edu 49 11 4 -7 -5 -16 -16 -15 -20 -11 -27 -1 -11 1 0 -0.2 Art.History 15 -6 -4 -2 -5 11 5 -13 -21 -2 -6 0 36 19 12 Other.PerfVisual.Art -3 -4 -11 -5 -6 12 7 4 -11 -10 -7 -10 4 31 -29 -0.4 Journalism 4 1 -9 2 -6 11 6 9 8 -9 13 -17 23 0 -5 Fine.Studio 11 -5 -16 -8 -8 17 10 -6 -12 -15 -16 -21 16 40 9 -0.6 Major.NA -8 -15 -22 -5 -9 -14 -19 5 -6 -20 -6 -16 -12 -2 -17 English 9 -7 -8 -13 -9 24 17 -17 -8 -11 -11 0 39 15 -4 -0.8 Art.Theory 8 -2 -8 -5 -9 13 6 -6 2 -5 -8 -17 6 42 -23 Fiction.Writing 6 -7 -16 -11 -12 23 11 -7 -11 2 2 -28 19 35 -6 -1 35 / 41 Introduction and overview SAPA methodology Results References

The relationship of personality and ability at the aggregate level

-0.1 0.1 -0.10 0.00 0.10 -0.2 0.2

Agreeable 0.2

0.55 0.68 -0.27 -0.63 -0.81 0.0 -0.2 Conscientious 0.1 0.59 0.32 -0.74 -0.62 -0.1

Extraversion 0.1

0.08 -0.54 -0.72 0.0 -0.2 Stability 0.10

0.00 -0.04 0.25 -0.10 Intellect 0.76 0.1 -0.1

FullIQ 0.2 -0.2

-0.2 0.0 0.2 -0.2 0.0 0.1 -0.1 0.1

36 / 41 Introduction and overview SAPA methodology Results References

Major groups by Ability and Stability

Engnrn 0.10

Busnss Tchnlg

0.05 Math

Cm.S.S Ntrl.S Md.A.H Eductn Stability Scl.Sc 0.00

Cmmnct

Cl.R.S

-0.05 Arts

Grp.NA Lngg.L

-0.2 -0.1 0.0 0.1 0.2 0.3

Ability 37 / 41 Introduction and overview SAPA methodology Results References

Major groups by Ability and Agreeableness

Md.A.H 0.15 Eductn Cm.S.S Scl.Sc 0.10 0.05 Cmmnct

0.00 Busnss Cl.R.S Arts Agreeableness -0.05

Lngg.LNtrl.S -0.10

Grp.NA

-0.15 Engnrn Tchnlg Math

-0.2 -0.1 0.0 0.1 0.2 0.3

Ability 38 / 41 Introduction and overview SAPA methodology Results References

Major groups by Ability and Conscientiousness

Md.A.H Busnss

Cm.S.S 0.1 Eductn

Scl.Sc Engnrn Ntrl.S 0.0

Cmmnct Tchnlg Extraversion Math

Cl.R.S

-0.1 Lngg.L Arts -0.2 Grp.NA

-0.2 -0.1 0.0 0.1 0.2 0.3

Ability 39 / 41 Introduction and overview SAPA methodology Results References Why are Ability and Temperament measures negatively correlated at the group level?

1 Compensatory selection will lead to a negative correlation Are Physicists selected to be disagreeable but smart Are educators selected be low on ability but highly agreeable? 2 Selection does not need to be compensatory, but merely extreme. If group A is selected for high ability, the mean score on other traits should be average If group B is selected for on Agreeableness, the mean scores on ability should be average This leads to a negative correlation between Ability and Agreeableness at the group level. 3 Feeback mechanisms are likely: people select into fields based upon differences in characteristics of the fields. What motivational interventions can we do to make STEM majors seem more agreeable?

40 / 41 Introduction and overview SAPA methodology Results References

Conclusion

1 Motivational choice can be seen in real world choices of college major Other examples include occupational choice 2 Using web based data techniques (e.g., SAPA), it is possible to do integrative studies of Temperament, Ability and Interests 3 Motivational choice reﬂects selection and compensation of temperament ability, and interests Majors that require high ability do not necessarily draw for socially adaptive traits Majors that require social skills do not necessarily draw for high ability

41 / 41 Introduction and overview SAPA methodology Results References

Ackerman, P. L. (1997). Personality, self-concept, interests, and intelligence: Which construct doesn’t ﬁt? Journal of Personality, 65(2), 171–204. Ackerman, P. L. & Heggestad, E. D. (1997). Intelligence, personality, and interests: Evidence for overlapping traits. Psychological Bulletin, 121(2), 219–245. Atkinson, J. W. & Birch, D. (1970). The dynamics of action. New York, N.Y.: John Wiley. Baltes, P. & Baltes, M. (1990). Psychological perspectives on successful aging: The model of selective optimization with compensation. Successful aging: Perspectives from the behavioral sciences, 1, 1–34. Deary, I. J., Penke, L., & Johnson, W. (2010). The neuroscience of human intelligence diﬀerences. Nature Reviews Neuroscience, 11(3), 201–211. Eysenck, H. J. (1990). Biological dimensions of personality. In L. A. Pervin (Ed.), Handbook of personality: Theory and research. (pp. 244–276). New York, NY: Guilford Press. 41 / 41 Introduction and overview SAPA methodology Results References

Fua, K., Horswill, I., Ortony, A., & Revelle, W. (2009). Reinforcement sensitivity theory and cognitive architectures. In Biologically Informed Cognitive Architectures (BICA-09), Washington, D.C. Fua, K., Revelle, W., & Ortony, A. (2010). Modeling personality and individual differences: the approach-avoid-conflict triad. In CogSci 2010: The Annual meeting of the Cognitive Science Society, Portland, Or. Goldberg, L. R. (1990). An alternative “description of personality”: The big-five factor structure. Journal of Personality and Social Psychology, 59(6), 1216–1229. Goldberg, L. R. (1999). A broad-bandwidth, public domain, personality inventory measuring the lower-level facets of several five-factor models. In I. Mervielde, I. Deary, F. De Fruyt, & F. Ostendorf (Eds.), Personality psychology in Europe, volume 7 (pp. 7–28). Tilburg, The Netherlands: Tilburg University Press. Gottfredson, L. S. (1997). Why g matters: The complexity of everyday life. Intelligence, 24(1), 79 – 132. 41 / 41 Introduction and overview SAPA methodology Results References

Hogan, R. (1982). A socioanalytic theory of personality. Nebraska Symposium on Motivation 1982, 55-89. Holland, J. L. (1996). Exploring careers with a typology: What we have learned and some new directions. American Psychologist, 51(4), 397 – 406. Horn, J. L. & Cattell, R. B. (1966). Refinement and test of the theory of fluid and crystallized general intelligences. Journal of Educational Psychology, 57(5), 253 – 270. Johnson, W. & Bouchard, T. J. (2005). The structure of human intelligence: It is verbal, perceptual, and image rotation (vpr), not fluid and crystallized. Intelligence, 33(4), 393 – 416. Kelly, E. L. & Fiske, D. W. (1950). The prediction of success in the VA training program in clinical psychology. American Psychologist, 5(8), 395 – 406. Kuncel, N. R., Campbell, J. P., & Ones, D. S. (1998). Validity of the graduate record examination: Estimated or tacitly known? American Psychologist, 53(5), 567–568. 41 / 41 Introduction and overview SAPA methodology Results References

Kuncel, N. R., Crede, M., & Thomas, L. L. (2005). The validity of self-reported grade point averages, class ranks, and test scores: A meta-analysis and review of the literature. Review of Educational Research, 75(1), 63–82. Kuncel, N. R., Hezlett, S. A., & Ones, D. S. (2001). A comprehensive meta-analysis of the predictive validity of the graduate record examinations: Implications for graduate student selection and performance. Psychological Bulletin, 127(1), 162 – 181. Lubinski, D. & Benbow, C. P. (2000). States of excellence. American Psychologist, 55(1), 137 – 150. Lubinski, D. & Benbow, C. P. (2006). Study of mathematically precocious youth after 35 years: Uncovering antecedents for the development of math-science expertise. Perspectives on Psychological Science, 1(4), 316–345. Lubinski, D., Webb, R., Morelock, M., & Benbow, C. (2001). Top 1 in 10,000: A 10-year follow-up of the profoundly gifted. Journal of applied Psychology, 86(4), 718–729. 41 / 41 Introduction and overview SAPA methodology Results References

Pozzebon, J. A., Visser, B. A., Ashton, M. C., Lee, K., & Goldberg, L. R. (2010). Psychometric characteristics of a public-domain self-report measure of vocational interests: The oregon vocational interest scales. Journal of Personality Assessment, 92(2), 168–? Prediger, D. J. & Vansickle, T. R. (1992). Locating occupations on holland’s hexagon: Beyond riasec. Journal of Vocational Behavior, 40(2), 111 – 128. Revelle, W. (1986). Motivation and efficiency of cognitive performance. In D. R. Brown & J. Veroff (Eds.), Frontiers of Motivational Psychology: Essays in honor of J. W. Atkinson chapter 7, (pp. 105–131). New York: Springer. Revelle, W., Wilt, J., & Rosenthal, A. (2010). Personality and cognition: The personality-cognition link. In A. Gruszka, G. Matthews, & B. Szymura (Eds.), Handbook of Individual Differences in Cognition: Attention, Memory and Executive Control chapter 2, (pp. 27–49). Springer.

41 / 41